AI for variant classification and clinical reporting

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Fabric Genomics Announces AI-based ACMG Classification Solution for Genetic Testing with Hereditary Panels

AI for variant classification and clinical reporting

SEATTLE--(BUSINESS WIRE)--Apr 1, 2019--Fabric Genomics will launch a new solution this week for variant interpretation and clinical reporting, allowing clinical laboratories to dramatically accelerate turnaround times. This new software solution, called Fabric Hereditary Panels with ACE (AI Classification Engine), will debut at the American College of Medical Genetics and Genomics (ACMG) annual meeting in Seattle, Washington. It incorporates an extensively validated, automated ACMG classification engine, enabling laboratories to speed up accurate variant classification and clinical reporting.



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Google AI variant caller goes deep on rice genomes

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Analyzing 3024 rice genomes characterized by DeepVariant

Google AI variant caller goes deep on rice genomes

“Rice is an ideal candidate for study in genomics, not only because it’s one of the world’s most important food crops, but also because centuries of agricultural cross-breeding have created unique, geographically-induced differences. With the potential for global population growth and climate change to impact crop yields, the study of this genome has important social considerations.

This post explores how to identify and analyze different rice genome mutations with a tool called DeepVariant. To do this, we performed a re-analysis of the Rice 3Kdataset and have made the data publicly available as part of the Google Cloud Public Dataset Program pre-publication and under the terms of the Toronto Statement.

We aim to show how AI can improve food security by accelerating genetic enhancement to increase rice crop yield. According to the Food and Agriculture Organization of the United Nations, crop improvements will reduce the negative impact of climate change and loss of arable land on rice yields, as well as support an estimated 25% increase in rice demand by 2030.”


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We'll need AI to deal with coming wave of genome data

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Getting smart about artificial intelligence

By: Alison Cranage, Science writer

We'll need AI to deal with coming wave of genome data. Genome Media.

“Genomics is set to become the biggest source of data on the planet, overtaking the current leading heavyweights – astronomy, YouTube and Twitter. Genome sequencing currently produces a staggering 25 petabytes of digital information per year. A petabyte is 1015 bytes, or about 1,000 times the average storage on a personal computer. And there is no sign of a slowdown.”


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Lucence improving personalized liver cancer treatment with AI

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Lucence Diagnostics to Develop AI Tools for Liver Cancer Treatment

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Lucence Diagnostics, a genomic medicine company focused on personalizing cancer care, today announced a new project to develop AI algorithms for improving diagnosis and treatment of liver cancer. The goal is to combine the imaging and molecular data from liver cancer patients into smarter software tools that help physicians make better treatment decisions.

Lucence will be working with Olivier Gevaert, PhD, Assistant Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science at the Stanford University School of Medicine. Having developed LiquidHALLMARK®, the world's first liquid biopsy next-generation sequencing test that analyzes the DNA of cancer-causing mutations and viruses, Lucence will contribute its genomics expertise and proprietary sequencing technology to this project.


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